Longitudinal study of a mouse model of chronic pulmonary inflammation using breath hold gated micro-CT

Stacking learning based on micro-CT radiomics for outcome prediction in the early-stage of silica-induced pulmonary fibrosis model

Silicosis is a progressive pulmonary fibrosis disease caused by long-term inhalation of silica. The early diagnosis and timely implementation of intervention measures are crucial in preventing silicosis deterioration further. However, the lack of screening and diagnostic measures for early-stage silicosis remains a significant challenge. In this study, silicosis models of varying severity were established through a single exposure to silica with different doses (2.5mg/mice or 5mg/mice) and durations (4 weeks or 12 weeks). The diagnostic performance of computed tomography (CT) quantitative analysis was assessed using lung density biomarkers and the lung density distribution histogram, with a particular focus on non-aerated lung volume. Subsequently, we developed and evaluated a stacking learning model for early diagnosis of silicosis after extracting and selecting features from CT images. The CT quantitative analysis reveals that while the lung densitometric biomarkers and lung density distribution histogram, as traditional indicators, effectively differentiate severe fibrosis models, they are unable to distinguish early-stage silicosis. Furthermore, these findings remained consistent even when employing non-aerated areas, which is a more sensitive indicator. By establishing a radiomics stacking learning model based on non-aerated areas, we can achieve remarkable diagnostic performance to distinguish early-stage silicosis, which can provide a valuable tool for clinical assistant diagnosis. This study reveals the potential of using non-aerated lung areas as a region of interest in stacking learning for early diagnosis of silicosis, providing new insights into early detection of this disease.

Application-specific approaches to MicroCT for evaluation of mouse models of pulmonary disease

The advent of micro-computed tomography (microCT) has provided significant advancement in our ability to generate clinically relevant assessments of lung health and disease in small animal models. As microCT use to generate outcomes analysis in pulmonary preclinical models has increased there have been substantial improvements in image quality and resolution, and data analysis software. However, there are limited published methods for standardized imaging and automated analysis available for investigators. Manual quantitative analysis of microCT images is complicated by the presence of inflammation and parenchymal disease. To improve the efficiency and limit user-associated bias, we have developed an automated pulmonary air and tissue segmentation (PATS) task list to segment lung air volume and lung tissue volume for quantitative analysis. We demonstrate the effective use of the PATS task list using four distinct methods for imaging, 1) in vivo respiration controlled scanning using a flexiVent, 2) longitudinal breath-gated in vivo scanning in resolving and non-resolving pulmonary disease initiated by lipopolysaccharide-, bleomycin-, and silica-exposure, 3) post-mortem imaging, and 4) ex vivo high-resolution scanning. The accuracy of the PATS task list was compared to manual segmentation. The use of these imaging techniques and automated quantification methodology across multiple models of lung injury and fibrosis demonstrates the broad applicability and adaptability of microCT to various lung diseases and small animal models and presents a significant advance in efficiency and standardization of preclinical microCT imaging and analysis for the field of pulmonary research.

Inhibition of antiapoptotic BCL-2 proteins with ABT-263 induces fibroblast apoptosis, reversing persistent pulmonary fibrosis

Patients with progressive fibrosing interstitial lung diseases (PF-ILDs) carry a poor prognosis and have limited therapeutic options. A hallmark feature is fibroblast resistance to apoptosis, leading to their persistence, accumulation, and excessive deposition of extracellular matrix. A complex balance of the B cell lymphoma 2 (BCL-2) protein family controlling the intrinsic pathway of apoptosis and fibroblast reliance on antiapoptotic proteins has been hypothesized to contribute to this resistant phenotype. Examination of lung tissue from patients with PF-ILD (idiopathic pulmonary fibrosis and silicosis) and mice with PF-ILD (repetitive bleomycin and silicosis) showed increased expression of antiapoptotic BCL-2 family members in α-smooth muscle actin-positive fibroblasts, suggesting that fibroblasts from fibrotic lungs may exhibit increased susceptibility to inhibition of antiapoptotic BCL-2 family members BCL-2, BCL-XL, and BCL-W with the BH3 mimetic ABT-263. We used 2 murine models of PF-ILD to test the efficacy of ABT-263 in reversing established persistent pulmonary fibrosis. Treatment with ABT-263 induced fibroblast apoptosis, decreased fibroblast numbers, and reduced lung collagen levels, radiographic disease, and histologically evident fibrosis. Our studies provide insight into how fibroblasts gain resistance to apoptosis and become sensitive to the therapeutic inhibition of antiapoptotic proteins. By targeting profibrotic fibroblasts, ABT-263 offers a promising therapeutic option for PF-ILDs.

Computed tomography reveals microenvironment changes in premetastatic lung

OBJECTIVES

Microenvironment changes had occurred in the metastatic organs before the arriving of the metastatic tumor cells. In this study, we evaluated the effectiveness of computed tomography (CT) images in quantifying the microenvironment changes in the premetastatic lung under both laboratory and clinical conditions.

METHOD

Free-breathing Balb/c mice underwent micro-CT repeatedly after the implantation of 4T1 breast tumor. CT-derived indicators (aerated lung volume, lung tissue volume, total lung volume, mean lung density, and the ratio of aerated lung volume to the total lung volume) were quantified. Hematoxylin-eosin staining was used to display the microenvironment changes in premetastatic lung. Moreover, we examined healthy adult women, adult women with histopathologically confirmed primary breast cancer, and adult women with histopathologically confirmed primary breast cancer and lung metastases in our institution to test whether the indicators derived from lung CT images changed with the growth of breast cancer.

RESULTS

In 4T1 tumor-bearing mice, lung density is increased before lung masses can be recognized on CT images and is correlated with the severity of inflammation in the lung microenvironment. In primary breast tumor-bearing patients, lung density is also increased before the clinical diagnosis of pulmonary metastasis and is correlated with disease score, which represents tumor progression.

CONCLUSIONS

CT is a reliable and quantitative tool that yields dynamic information on metastatic processes. Microenvironmental changes had occurred in patients' lung tissue before the clinical diagnosis of pulmonary metastasis. Our research will provide new insight for clinical research on the premetastatic niche.

KEY POINTS

• CT, which provides dynamic information on metastatic processes, is a reliable and quantitative tool to bridge laboratory and clinical studies of the premetastatic niche. • We confirmed that microenvironmental changes occurred in patients' lung tissue before clinicians could diagnose pulmonary metastasis. • Our results provide evidence for the study of the premetastatic niche by analyzing information obtained from CT images.

Longitudinal micro-computed tomography-derived biomarkers quantify non-resolving lung fibrosis in a silicosis mouse model

In spite of many compounds identified as antifibrotic in preclinical studies, pulmonary fibrosis remains a life-threatening condition for which highly effective treatment is still lacking. Towards improving the success-rate of bench-to-bedside translation, we investigated in vivo µCT-derived biomarkers to repeatedly quantify experimental silica-induced pulmonary fibrosis and assessed clinically relevant readouts up to several months after silicosis induction. Mice were oropharyngeally instilled with crystalline silica or saline and longitudinally monitored with respiratory-gated-high-resolution µCT to evaluate disease onset and progress using scan-derived biomarkers. At weeks 1, 5, 9 and 15, we assessed lung function, inflammation and fibrosis in subsets of mice in a cross-sectional manner. Silica-instillation increased the non-aerated lung volume, corresponding to onset and progression of inflammatory and fibrotic processes not resolving with time. Moreover, total lung volume progressively increased with silicosis. The volume of healthy, aerated lung first dropped then increased, corresponding to an acute inflammatory response followed by recovery into lower elevated aerated lung volume. Imaging results were confirmed by a significantly decreased Tiffeneau index, increased neutrophilic inflammation, increased IL-13, MCP-1, MIP-2 and TNF-α concentration in bronchoalveolar lavage fluid, increased collagen content and fibrotic nodules. µCT-derived biomarkers enable longitudinal evaluation of early onset inflammation and non-resolving pulmonary fibrosis as well as lung volumes in a sensitive and non-invasive manner. This approach and model of non-resolving lung fibrosis provides quantitative assessment of disease progression and stabilization over weeks and months, essential towards evaluation of fibrotic disease burden and antifibrotic therapy evaluation in preclinical studies.

Unsupervised CT Lung Image Segmentation of a Mycobacterium Tuberculosis Infection Model

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis that produces pulmonary damage. Radiological imaging is the preferred technique for the assessment of TB longitudinal course. Computer-assisted identification of biomarkers eases the work of the radiologist by providing a quantitative assessment of disease. Lung segmentation is the step before biomarker extraction. In this study, we present an automatic procedure that enables robust segmentation of damaged lungs that have lesions attached to the parenchyma and are affected by respiratory movement artifacts in a Mycobacterium Tuberculosis infection model. Its main steps are the extraction of the healthy lung tissue and the airway tree followed by elimination of the fuzzy boundaries. Its performance was compared with respect to a segmentation obtained using: (1) a semi-automatic tool and (2) an approach based on fuzzy connectedness. A consensus segmentation resulting from the majority voting of three experts' annotations was considered our ground truth. The proposed approach improves the overlap indicators (Dice similarity coefficient, 94% ± 4%) and the surface similarity coefficients (Hausdorff distance, 8.64 mm ± 7.36 mm) in the majority of the most difficult-to-segment slices. Results indicate that the refined lung segmentations generated could facilitate the extraction of meaningful quantitative data on disease burden.

Inhibition of ataxia telangiectasia related-3 (ATR) improves therapeutic index in preclinical models of non-small cell lung cancer (NSCLC) radiotherapy

BACKGROUND AND PURPOSE

To evaluate the impact of ATR inhibition using AZD6738 in combination with radiotherapy on the response of non-small cell lung cancer (NSCLC) tumour models and a murine model of radiation induced fibrosis.

MATERIALS AND METHODS

AZD6738 was evaluated as a monotherapy and in combination with radiation in vitro and in vivo using A549 and H460 NSCLC models. Radiation induced pulmonary fibrosis was evaluated by cone beam computed tomography (CBCT) and histological staining.

RESULTS

AZD6738 specifically inhibits ATR kinase and enhanced radiobiological response in NSCLC models but not in human bronchial epithelial cells (HBECs) in vitro. Significant tumour growth delay was observed in cell line derived xenografts (CDXs) of H460 cells (p<0.05) which were less significant in A549 cells. Combination of AZD6738 with radiotherapy showed no significant change in lung tissue density by CBCT (p>0.5) and histological scoring of radiation induced fibrosis (p>0.5).

CONCLUSION

Inhibition of ATR with AZD6738 in combination with radiotherapy increases tumour growth delay without observable augmentation of late radiation induced toxicity further underpinning translation towards clinical evaluation in NSCLC.

Effects of nintedanib on the microvascular architecture in a lung fibrosis model

Nintedanib, a tyrosine kinase inhibitor approved for the treatment of idiopathic pulmonary fibrosis, has anti-fibrotic, anti-inflammatory, and anti-angiogenic activity. We explored the impact of nintedanib on microvascular architecture in a pulmonary fibrosis model. Lung fibrosis was induced in C57Bl/6 mice by intratracheal bleomycin (0.5 mg/kg). Nintedanib was started after the onset of lung pathology (50 mg/kg twice daily, orally). Micro-computed tomography was performed via volumetric assessment. Static lung compliance and forced vital capacity were determined by invasive measurements. Mice were subjected to bronchoalveolar lavage and histologic analyses, or perfused with a casting resin. Microvascular corrosion casts were imaged by scanning electron microscopy and synchrotron radiation tomographic microscopy, and quantified morphometrically. Bleomycin administration resulted in a significant increase in higher-density areas in the lungs detected by micro-computed tomography, which was significantly attenuated by nintedanib. Nintedanib significantly reduced lung fibrosis and vascular proliferation, normalized the distorted microvascular architecture, and was associated with a trend toward improvement in lung function and inflammation. Nintedanib resulted in a prominent improvement in pulmonary microvascular architecture, which outperformed the effect of nintedanib on lung function and inflammation. These findings uncover a potential new mode of action of nintedanib that may contribute to its efficacy in idiopathic pulmonary fibrosis.

Quantification of Pulmonary Fibrosis in a Bleomycin Mouse Model Using Automated Histological Image Analysis

Current literature on pulmonary fibrosis induced in animal models highlights the need of an accurate, reliable and reproducible histological quantitative analysis. One of the major limits of histological scoring concerns the fact that it is observer-dependent and consequently subject to variability, which may preclude comparative studies between different laboratories. To achieve a reliable and observer-independent quantification of lung fibrosis we developed an automated software histological image analysis performed from digital image of entire lung sections. This automated analysis was compared to standard evaluation methods with regard to its validation as an end-point measure of fibrosis. Lung fibrosis was induced in mice by intratracheal administration of bleomycin (BLM) at 0.25, 0.5, 0.75 and 1 mg/kg. A detailed characterization of BLM-induced fibrosis was performed 14 days after BLM administration using lung function testing, micro-computed tomography and Ashcroft scoring analysis. Quantification of fibrosis by automated analysis was assessed based on pulmonary tissue density measured from thousands of micro-tiles processed from digital images of entire lung sections. Prior to analysis, large bronchi and vessels were manually excluded from the original images. Measurement of fibrosis has been expressed by two indexes: the mean pulmonary tissue density and the high pulmonary tissue density frequency. We showed that tissue density indexes gave access to a very accurate and reliable quantification of morphological changes induced by BLM even for the lowest concentration used (0.25 mg/kg). A reconstructed 2D-image of the entire lung section at high resolution (3.6 μm/pixel) has been performed from tissue density values allowing the visualization of their distribution throughout fibrotic and non-fibrotic regions. A significant correlation (p<0.0001) was found between automated analysis and the above standard evaluation methods. This correlation establishes automated analysis as a novel end-point measure of BLM-induced lung fibrosis in mice, which will be very valuable for future preclinical drug explorations.

Computer-aided pulmonary image analysis in small animal models

PURPOSE

To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models.

METHODS

The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors' system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next. The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters.

RESULTS

133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT'09 data set.

CONCLUSIONS

The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases.

Longitudinal micro-CT provides biomarkers of lung disease that can be used to assess the effect of therapy in preclinical mouse models, and reveal compensatory changes in lung volume

In vivo lung micro-computed tomography (micro-CT) is being increasingly embraced in pulmonary research because it provides longitudinal information on dynamic disease processes in a field in which ex vivo assessment of experimental disease models is still the gold standard. To optimize the quantitative monitoring of progression and therapy of lung diseases, we evaluated longitudinal changes in four different micro-CT-derived biomarkers [aerated lung volume, lung tissue (including lesions) volume, total lung volume and mean lung density], describing normal development, lung infections, inflammation, fibrosis and therapy. Free-breathing mice underwent micro-CT before and repeatedly after induction of lung disease (bleomycin-induced fibrosis, invasive pulmonary aspergillosis, pulmonary cryptococcosis) and therapy (imatinib). The four lung biomarkers were quantified. After the last time point, we performed pulmonary function tests and isolated the lungs for histology. None of the biomarkers remained stable during longitudinal follow-up of adult healthy mouse lungs, implying that biomarkers should be compared with age-matched controls upon intervention. Early inflammation and progressive fibrosis led to a substantial increase in total lung volume, which affects the interpretation of aerated lung volume, tissue volume and mean lung density measures. Upon treatment of fibrotic lung disease, the improvement in aerated lung volume and function was not accompanied by a normalization of the increased total lung volume. Significantly enlarged lungs were also present in models of rapidly and slowly progressing lung infections. The data suggest that total lung volume changes could partly reflect a compensatory mechanism that occurs during disease progression in mice. Our findings underscore the importance of quantifying total lung volume in addition to aerated lung or lesion volumes to accurately document growth and potential compensatory mechanisms in mouse models of lung disease, in order to fully describe and understand dynamic processes during lung disease onset, progression and therapy. This is highly relevant for the translation of therapy evaluation results from preclinical studies to human patients.

In vivo small animal micro-CT using nanoparticle contrast agents

Computed tomography (CT) is one of the most valuable modalities for in vivo imaging because it is fast, high-resolution, cost-effective, and non-invasive. Moreover, CT is heavily used not only in the clinic (for both diagnostics and treatment planning) but also in preclinical research as micro-CT. Although CT is inherently effective for lung and bone imaging, soft tissue imaging requires the use of contrast agents. For small animal micro-CT, nanoparticle contrast agents are used in order to avoid rapid renal clearance. A variety of nanoparticles have been used for micro-CT imaging, but the majority of research has focused on the use of iodine-containing nanoparticles and gold nanoparticles. Both nanoparticle types can act as highly effective blood pool contrast agents or can be targeted using a wide variety of targeting mechanisms. CT imaging can be further enhanced by adding spectral capabilities to separate multiple co-injected nanoparticles in vivo. Spectral CT, using both energy-integrating and energy-resolving detectors, has been used with multiple contrast agents to enable functional and molecular imaging. This review focuses on new developments for in vivo small animal micro-CT using novel nanoparticle probes applied in preclinical research.

Three-dimensional accurate detection of lung emphysema in rats using ultra-short and zero echo time MRI

Emphysema is a life-threatening pathology that causes irreversible destruction of alveolar walls. In vivo imaging techniques play a fundamental role in the early non-invasive pre-clinical and clinical detection and longitudinal follow-up of this pathology. In the present study, we aimed to evaluate the feasibility of using high resolution radial three-dimensional (3D) zero echo time (ZTE) and 3D ultra-short echo time (UTE) MRI to accurately detect lung pathomorphological changes in a rodent model of emphysema.Porcine pancreas elastase (PPE) was intratracheally administered to the rats to produce the emphysematous changes. 3D ZTE MRI, low and high definition 3D UTE MRI and micro-computed tomography images were acquired 4 weeks after the PPE challenge. Signal-to-noise ratios (SNRs) were measured in PPE-treated and control rats. T2* values were computed from low definition 3D UTE MRI. Histomorphometric measurements were made after euthanizing the animals. Both ZTE and UTE MR images showed a significant decrease in the SNR measured in PPE-treated lungs compared with controls, due to the pathomorphological changes taking place in the challenged lungs. A significant decrease in T2* values in PPE-challenged animals compared with controls was measured using UTE MRI. Histomorphometric measurements showed a significant increase in the mean linear intercept in PPE-treated lungs. UTE yielded significantly higher SNR compared with ZTE (14% and 30% higher in PPE-treated and non-PPE-treated lungs, respectively).This study showed that optimized 3D radial UTE and ZTE MRI can provide lung images of excellent quality, with high isotropic spatial resolution (400 µm) and SNR in parenchymal tissue (>25) and negligible motion artifacts in freely breathing animals. These techniques were shown to be useful non-invasive instruments to accurately and reliably detect the pathomorphological alterations taking place in emphysematous lungs, without incurring the risks of cumulative radiation exposure typical of micro-computed tomography.

Optical coherence tomography in respiratory science and medicine: from airways to alveoli

Optical coherence tomography is a rapidly maturing optical imaging technology, enabling study of the in vivo structure of lung tissue at a scale of tens of micrometers. It has been used to assess the layered structure of airway walls, quantify both airway lumen caliber and compliance, and image individual alveoli. This article provides an overview of the technology and reviews its capability to provide new insights into respiratory disease.

Characterization of spontaneous air space enlargement in mice lacking microfibrillar-associated protein 4

Microfibrillar-associated protein 4 (MFAP4) is localized to elastic fibers in blood vessels and the interalveolar septa of the lungs and is further present in bronchoalveolar lavage. Mfap4 has been previously suggested to be involved in elastogenesis in the lung. We tested this prediction and aimed to characterize the pulmonary function changes and emphysematous changes that occur in Mfap4-deficient (Mfap4(-/-)) mice. Significant changes included increases in total lung capacity and compliance, which were evident in Mfap4(-/-) mice at 6 and 8 mo but not at 3 mo of age. Using in vivo breath-hold gated microcomputed tomography (micro-CT) in 8-mo-old Mfap4(-/-) mice, we found that the mean density of the lung parenchyma was decreased, and the low-attenuation area (LAA) was significantly increased by 14% compared with Mfap4(+/+) mice. Transmission electron microscopy (TEM) did not reveal differences in the organization of elastic fibers, and there was no difference in elastin content, but a borderline significant increase in elastin mRNA expression in 3-mo-old mice. Stereological analysis showed that alveolar surface density in relation to the lung parenchyma and total alveolar surface area inside of the lung were both significantly decreased in Mfap4(-/-) mice by 25 and 15%, respectively. The data did not support an essential role of MFAP4 in pulmonary elastic fiber organization or content but indicated increased turnover in young Mfap4(-/-) mice. However, Mfap4(-/-) mice developed a spontaneous loss of lung function, which was evident at 6 mo of age, and moderate air space enlargement, with emphysema-like changes.

A longitudinal evaluation of partial lung irradiation in mice by using a dedicated image-guided small animal irradiator

PURPOSE

In lung cancer radiation therapy, the dose constraints are determined mostly by healthy lung toxicity. Preclinical microirradiators are a new tool to evaluate treatment strategies closer to clinical irradiation devices. In this study, we quantified local changes in lung density symptomatic of radiation-induced lung fibrosis (RILF) after partial lung irradiation in mice by using a precision image-guided small animal irradiator integrated with micro-computed tomography (CT) imaging.

METHODS AND MATERIALS

C57BL/6 adult male mice (n=76) were divided into 6 groups: a control group (0 Gy) and groups irradiated with a single fraction of 4, 8, 12, 16, or 20 Gy using 5-mm circular parallel-opposed fields targeting the upper right lung. A Monte Carlo model of the small animal irradiator was used for dose calculations. Following irradiation, all mice were imaged at regular intervals over 39 weeks (10 time points total). Nonrigid deformation was used to register the initial micro-CT scan to all subsequent scans.

RESULTS

Significant differences could be observed between the 3 highest (>10 Gy) and 3 lowest irradiation (<10 Gy) dose levels. A mean difference of 120 ± 10 HU between the 0- and 20-Gy groups was observed at week 39. RILF was found to be spatially limited to the irradiated portion of the lung.

CONCLUSIONS

The data suggest that the severity of RILF in partial lung irradiation compared to large field irradiation in mice for the same dose is reduced, and therefore higher doses can be tolerated.

Preclinical anatomical, molecular, and functional imaging of the lung with multiple modalities

In vivo imaging is an important tool for preclinical studies of lung function and disease. The widespread availability of multimodal animal imaging systems and the rapid rate of diagnostic contrast agent development have empowered researchers to noninvasively study lung function and pulmonary disorders. Investigators can identify, track, and quantify biological processes over time. In this review, we highlight the fundamental principles of bioluminescence, fluorescence, planar X-ray, X-ray computed tomography, magnetic resonance imaging, and nuclear imaging modalities (such as positron emission tomography and single photon emission computed tomography) that have been successfully employed for the study of lung function and pulmonary disorders in a preclinical setting. The major principles, benefits, and applications of each imaging modality and technology are reviewed. Limitations and the future prospective of multimodal imaging in pulmonary physiology are also discussed. In vivo imaging bridges molecular biological studies, drug design and discovery, and the imaging field with modern medical practice, and, as such, will continue to be a mainstay in biomedical research.

Contrasting responses of non-small cell lung cancer to antiangiogenic therapies depend on histological subtype

The vascular endothelial growth factor (VEGF) pathway is a clinically validated antiangiogenic target for non-small cell lung cancer (NSCLC). However, some contradictory results have been reported on the biological effects of antiangiogenic drugs. In order to evaluate the efficacy of these drugs in NSCLC histological subtypes, we analyzed the anticancer effect of two anti-VEGFR2 therapies (sunitinib and DC101) in chemically induced mouse models and tumorgrafts of lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Antiangiogenic treatments induced vascular trimming in both histological subtypes. In ADC tumors, vascular trimming was accompanied by tumor stabilization. In contrast, in SCC tumors, antiangiogenic therapy was associated with disease progression and induction of tumor proliferation. Moreover, in SCC, anti-VEGFR2 therapies increased the expression of stem cell markers such as aldehyde dehydrogenase 1A1, CD133, and CD15, independently of intratumoral hypoxia. In vitro studies with ADC cell lines revealed that antiangiogenic treatments reduced pAKT and pERK signaling and inhibited proliferation, while in SCC-derived cell lines the same treatments increased pAKT and pERK, and induced survival. In conclusion, this study evaluates for the first time the effect of antiangiogenic drugs in lung SCC murine models in vivo and sheds light on the contradictory results of antiangiogenic therapies in NSCLC.

Growth pattern analysis of murine lung neoplasms by advanced semi-automated quantification of micro-CT images

Computed tomography (CT) is a non-invasive imaging modality used to monitor human lung cancers. Typically, tumor volumes are calculated using manual or semi-automated methods that require substantial user input, and an exponential growth model is used to predict tumor growth. However, these measurement methodologies are time-consuming and can lack consistency. In addition, the availability of datasets with sequential images of the same tumor that are needed to characterize in vivo growth patterns for human lung cancers is limited due to treatment interventions and radiation exposure associated with multiple scans. In this paper, we performed micro-CT imaging of mouse lung cancers induced by overexpression of ribonucleotide reductase, a key enzyme in nucleotide biosynthesis, and developed an advanced semi-automated algorithm for efficient and accurate tumor volume measurement. Tumor volumes determined by the algorithm were first validated by comparison with results from manual methods for volume determination as well as direct physical measurements. A longitudinal study was then performed to investigate in vivo murine lung tumor growth patterns. Individual mice were imaged at least three times, with at least three weeks between scans. The tumors analyzed exhibited an exponential growth pattern, with an average doubling time of 57.08 days. The accuracy of the algorithm in the longitudinal study was also confirmed by comparing its output with manual measurements. These results suggest an exponential growth model for lung neoplasms and establish a new advanced semi-automated algorithm to measure lung tumor volume in mice that can aid efforts to improve lung cancer diagnosis and the evaluation of therapeutic responses.

Oscillation mechanics of the respiratory system

The mechanical impedance of the respiratory system defines the pressure profile required to drive a unit of oscillatory flow into the lungs. Impedance is a function of oscillation frequency, and is measured using the forced oscillation technique. Digital signal processing methods, most notably the Fourier transform, are used to calculate impedance from measured oscillatory pressures and flows. Impedance is a complex function of frequency, having both real and imaginary parts that vary with frequency in ways that can be used empirically to distinguish normal lung function from a variety of different pathologies. The most useful diagnostic information is gained when anatomically based mathematical models are fit to measurements of impedance. The simplest such model consists of a single flow-resistive conduit connecting to a single elastic compartment. Models of greater complexity may have two or more compartments, and provide more accurate fits to impedance measurements over a variety of different frequency ranges. The model that currently enjoys the widest application in studies of animal models of lung disease consists of a single airway serving an alveolar compartment comprising tissue with a constant-phase impedance. This model has been shown to fit very accurately to a wide range of impedance data, yet contains only four free parameters, and as such is highly parsimonious. The measurement of impedance in human patients is also now rapidly gaining acceptance, and promises to provide a more comprehensible assessment of lung function than parameters derived from conventional spirometry.

Individual nodule tracking in micro-CT images of a longitudinal lung cancer mouse model

We present and evaluate an automatic and quantitative method for the complex task of characterizing individual nodule volumetric progression in a longitudinal mouse model of lung cancer. Fourteen A/J mice received an intraperitoneal injection of urethane. Respiratory-gated micro-CT images of the lungs were acquired at 8, 22, and 37 weeks after injection. A radiologist identified a total of 196, 585 and 636 nodules, respectively. The three micro-CT image volumes from every animal were then registered and the nodules automatically matched with an average accuracy of 99.5%. All nodules detected at week 8 were tracked all the way to week 37, and volumetrically segmented to measure their growth and doubling rates. 92.5% of all nodules were correctly segmented, ranging from the earliest stage to advanced stage, where nodule segmentation becomes more challenging due to complex anatomy and nodule overlap. Volume segmentation was validated using a foam lung phantom with embedded polyethylene microspheres. We also correlated growth rates with nodule phenotypes based on histology, to conclude that the growth rate of malignant tumors is significantly higher than that of benign lesions. In conclusion, we present a turnkey solution that combines longitudinal imaging with nodule matching and volumetric nodule segmentation resulting in a powerful tool for preclinical research.

Quantification of lung damage in an elastase-induced mouse model of emphysema

Objective. To define the sensitivity of microcomputed tomography- (micro-CT-) derived descriptors for the quantification of lung damage caused by elastase instillation. Materials and Methods. The lungs of 30 elastase treated and 30 control A/J mice were analyzed 1, 6, 12, and 24 hours and 7 and 17 days after elastase instillation using (i) breath-hold-gated micro-CT, (ii) pulmonary function tests (PFTs), (iii) RT-PCR for RNA cytokine expression, and (iv) histomorphometry. For the latter, an automatic, parallel software toolset was implemented that computes the airspace enlargement descriptors: mean linear intercept (L(m)) and weighted means of airspace diameters (D(0), D(1), and D(2)). A Support Vector Classifier was trained and tested based on three nonhistological descriptors using D(2) as ground truth. Results. D(2) detected statistically significant differences (P < 0.01) between the groups at all time points. Furthermore, D(2) at 1 hour (24 hours) was significantly lower (P < 0.01) than D(2) at 24 hours (7 days). The classifier trained on the micro-CT-derived descriptors achieves an area under the curve (AUC) of 0.95 well above the others (PFTS AUC = 0.71; cytokine AUC = 0.88). Conclusion. Micro-CT-derived descriptors are more sensitive than the other methods compared, to detect in vivo early signs of the disease.